The present invention relates to methods of detecting and quantifying rare nucleic acids changes, mutations or polymorphisms in a nucleic acid sample; namely, the sample contains a much smaller percentage of the changed, mutated or polymorphic nucleic acid molecule compared to that of the wildtype or more common variants or control nucleic acid molecules.
Detection of a nucleic acid containing a rare polymorphism or mutation can be problematic. Such problems occur in numerous situations, for example, if a nucleic acid sample is suspected of containing a small population of mutant nucleic acids such as in diagnosis or prognosis of cancer, viral infections, variations in viral infections, such as various HIV strains in the same individual, and the like. In all these cases, it is important to know accurately whether the nucleic acid sample actually contains the rare mutant allele or not, and in many cases it would be helpful to know how much mutant allele containing nucleic acid is present in the sample, particularly in relation to the wildtype or the more common nucleic acid molecule.
Methods for detection and quantification of nucleic acids that contain differences which are present in only low quantities or small percentages compared to a wildtype or control nucleic acid molecule in the sample can be important in many clinical applications. Non-limiting examples of applications wherein detection of rare nucleic acid changes would be useful include early benign or malignant tumor detection, prenatal diagnostics particularly when using a plasma or serum DNA sample from the mother, early viral or bacterial disease detection, environmental monitoring, monitoring of effects of pharmaceutical interventions such as early detection of multi drug resistance mutations in cancer treatment. Also, a number of mutations causing inherited diseases result in reduction of the transcript levels. Therefore, improved methods allowing detection of the mutant transcript which is present at very low levels would allow a simplification of mutation detection, particularly at the RNA level, in cases wherein the mutant transcript levels are low.
Detection of rare mutations could also provide tools for forensic nucleic acid sample analysis by providing a system to reliably detect presence or absence of specific nucleic acid polymorphisms to provide evidence to exonerate a crime suspect.
Additionally, detection of rare mutations in biological agents such as bacteria and viruses that can be used as a biological warfare agents would provide an important tool for detecting spread of harmful biological materials.
Another problem requiring a satisfactory solution is in the commonly used genotyping methods, is a so called “allele dropout”-problem which happens when one allele is poorly amplified or detected and a heterozygotic allele is mis-called as a homozygote. The dropout allele is usually, but not always, the allele that produces a higher molecular weight base extension product. A method which would allow the detection of allele dropout, particularly in clinical diagnostic applications, would be extremely useful and improve the accuracy of distinguishing heterozygotes from homozygotes, which can be crucial for evaluating, for example, disease prognosis.
The methods for mutation detection and nucleic acid molecule quantification have traditionally included Southern-blot and Northern-blot hybridization, ribonuclease protection assay, and polymerase chain reaction (PCR) and reverse transcriptase PCR (RT-PCR) based methods. However, both direct detection methods and PCR-based methods to detect nucleic acid molecules suffer from lack of sensitivity to detect or amplify the rare nucleic acid mutation, when the sample nucleic acid contains both a large amount of the wildtype nucleic acids and a much smaller amount of the rare mutation or polymorphism.
Absolute quantification of nucleic acid molecule copy numbers in a sample is a requirement if one wishes to monitor the number of mutant or polymorphic nucleic acids, for example, at different time points or as a response to a pharmaceutical intervention. However, quantification of nucleic acid copy numbers for rare mutations is difficult using PCR based methods because the common nucleic acid molecule is also amplified exponentially and the mixture of amplified sample almost always contains large amounts of the wildtype or “normal” nucleic acid variant relative to the rare nucleic acid variant.
A number of quantitative PCR based methods have been described including RNA quantification using PCR and complementary DNA (cDNA) arrays (Shalon et al., Genome Research 6(7):639-45, 1996; Bernard et al., Nucleic Acids Research 24(8):1435-42, 1996), solid-phase mini-sequencing technique, which is based upon a primer extension reaction (U.S. Pat. No. 6,013,431, Suomalainen et al. Mol. Biotechnol. June; 15(2):123-31, 2000), ion-pair high-performance liquid chromatography (Doris et al. J. Chromatogr. A May 8; 806(1):47-60, 1998), 5′ nuclease assay or real-time RT-PCR (Holland et al. Proc Natl Acad Sci USA 88: 7276-7280, 1991), and real competitive RT-PCR (Ding et al. Proc Natl Acad Sci USA 100:3059-3064, 2003).
Methods using PCR and internal standards differing by length or restriction endonuclease site from the desired target sequence allowing comparison of the standard with the target using gel electrophoretic separation methods followed by densitometric quantification of the target have also been developed (see, e.g., U.S. Pat. Nos. 5,876,978; 5,643,765; and 5,639,606). These methods, also sometimes referred to as StaRT-PCT, have severe limitations in measuring an absolute transcript quantity in a biological sample. Because of the size differences between the standard and the target sequence, the PCR amplification can not be expected to be the same for both the standard and the target sequence. Further, because a separate gel electrophoretic separation and/or restriction endonuclease digestion followed by gel electrophoretic separation, and densitometric measurement are required after amplification, the method has steps which are prone to errors and make the quantification of small amounts of nucleic acids cumbersome.
Therefore, it would be useful to develop a method which allows sensitive and accurate detection and quantification of nucleic acids containing rare changes and which can be easily automated and scaled up to accommodate testing of large numbers of sample and which overcome the sensitivity problems of nucleic acid detection. Such a method would enable diagnosing different pathological conditions, including viruses, bacteria and parasites, as well as different benign and malignant tumors, neurological disorders, heart disease and autoimmune disorders. Such a method would also allow quantifying the rare transcripts of interest for diagnostic, prognostic and therapeutic purposes.